survival of red desert pronghorn in the face of ... · steve perry survival of red desert pronghorn...
TRANSCRIPT
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Steve Perry
Survival of Red Desert Pronghorn in the Face of Environmental and Anthropogenic Change
Adele K. Reinking1, Jeffrey L. Beck1, Tony W. Mong2, Mary J. Read3, and Kevin L. Monteith4
1Department of Ecosystem Science and Management, University of Wyoming, 1000 E. University Avenue, Laramie, WY 82071 2Wyoming Game and Fish Department, P.O. Box 116, Savery, WY 82332
3Bureau of Land Management, 1300 3rd Street, Rawlins, WY 82301 4Haub School of Environment and Natural Resources, Wyoming Cooperative Fish and Wildlife Research Unit, Department of
Zoology and Physiology, University of Wyoming, 1000 E. University Avenue, Laramie, WY 82071
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Wyoming pronghorn
audubon.org
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The Red Desert
wyofiles.com
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The Red Desert
Bitter Creek herd
Baggs herd
Red Desert herd
Red Desert
Bitter Creek
CDC
Baggs
Baggs
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The Red Desert
wyofiles.com
wyofiles.com
ncdc.noaa.gov
National Oceanic and Atmospheric
Administration (NOAA) Climate Divisions for
State of Wyoming
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The Red Desert
Red Desert
Bitter Creek
CDC
Baggs
Baggs
0.57/km2
0−5.8/km2
0.18/km2
0−5.1/km2 0.53/km2
0−13.7/km2
0.15/km2
0−8.2/km2
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Mortality risk statistics
93
31
0102030405060708090
100110120130140
Num
ber
of e
vent
s
Modeling events
Died
Survived
Basic statistics: • 186 adult female pronghorn collared • 80% of deaths occurred in summer • 124 females included in summer modeling • GPS-collared individuals
• 2 hour fix rate • 2 years
0
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0.8
1
11/1
0/20
13
12/1
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13
1/10
/201
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2/10
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4
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10/1
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14
11/1
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12/1
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14
1/10
/201
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2/10
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0/20
15
11/1
0/20
15
12/1
0/20
15
1/10
/201
6
Surv
ival
Date
Daily Red Desert Pronghorn Survival Median Survival= 0.75
Survival
Lower CI
Upper CI
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Mortality Risk Hypotheses
1) Habitat quality
2) Anthropogenic conditions
3) Intrinsic factors
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roadsendnaturalist.com
Robbins & Robbins 1979
Hypothesis 1: Habitat quality
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Northern Focus Photography
usgs.gov
Hypothesis 1: Habitat quality
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goeddelphotography.com
Hypothesis 1: Habitat quality
Mautz 1978
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Hypothesis 1: Habitat quality roadsendnaturalist.com
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county10.com
Hypothesis 1: Habitat quality
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Predicted Explanatory Covariates
Climate Sagebrush
commons.wikimedia.org
audubon.org
Joe Riis
Fat Reserves
Distance to water
Precipitation (time lag)
Temperature (time lag)
Proportion locations in sagebrush (seasonally)
Hypothesis 1: Habitat quality
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eurekalert.org
Polfus et al. (2011)
Beckmann et al. (2012)
hcn.org
Sawyer et al. (2009)
Hypothesis 2: Anthropogenic conditions
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Hypothesis 2: Anthropogenic conditions
Joe Riis
sciencedaily.com
earthisland.org
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Predicted Explanatory Covariates
Roads Wells
Fat Reserves
Distance Density
Fences
Hypothesis 2: Anthropogenic conditions
Joe Riis
Joe Riis
onthewingphotography.com
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Fat Reserves
Sacrosciatic Ligament
Palpation Sacrum
Caudal Vertebrae
Lumbar Vertebrae
Bicep Femoris
Longissimus Dorsi
Maximum Rump Fat
Ultrasonography
digital-images.net
Base of Tail
Hypothesis 3: Intrinsic factors
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1
2
Estimated Age
Corrected Age 0.7855*Est. Age + 2.00093
Hypothesis 3: Intrinsic factors deerhuntingpros.com
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Modeling approach
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Modeling results
canada-hunts.ca
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Modeling results
Mortality risk increases with: Proportion time spent in sagebrush during previous winter (p-value = 0.013) Total terrain ruggedness for the week (p-value < 0.001) Variation in snow depth during previous winter (p- value = 0.076)
billingsgazette.com ?
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Discussion
Joe Riis
skyhidailynews.com
Proportion time spent in sagebrush
during previous winter
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Future directions
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Thank you to our funders
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Dr. Jeff Beck Dr. Kevin Monteith & Tony Mong Kim Olson
Dr. Derek Scasta Dr. Shannon Albeke
Others:
Beck lab Many other WGFD folks Mary Read Frank Blomquist Many other BLM folks Jack Taylor Gary Sundberg Cory Reinking
Jacob Pelham Bryan Lamont Melanie LaCava Melinda Nelson Preston Foote McCall Calvert Zachary Robinson Missy Stallard
Teal Joseph
Dr. Holly Ernest
Many others to thank
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TITLE
Jansen Gunderson
The Red Desert
0
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Objective
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Popu
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Red Desert Herd Population Trend
Actual
Objective
Red Desert
Bitter Creek Baggs
CDC Baggs
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Modeling approach
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Model Name
K AICc Delta AICc
Model Likelihood
AICc Weight
Log Likelihood
Cumulative Weight
Study Area
1 256.68 0.00 1.00 0.40 -127.34 0.40
Year + Study Area
2 258.50 1.82 0.40 0.16 -127.25 0.55
Individual + Study Area
2 258.62 1.94 0.38 0.15 -127.31 0.70
Year 1 258.75 2.07 0.36 0.14 -128.37 0.85
Individual 1 259.37 2.69 0.26 0.10 -128.69 0.95
Individual + Year
2 260.75 4.07 0.13 0.05 -128.37 1.00
Random Effect Coefficient
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Modeling approach
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Non-Collinear Covariates ranking above the null model • Total terrain ruggedness for the week • Total distance to roads for the week • Total fence density at the 5km scale for the week • Total distance to wells for the week • Total distance to water for the week • Variation in snow depth during the previous winter • Sacrosciatic ligament depth • Proportion time spent in sagebrush during the
previous winter • Estimated Age
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Modeling approach
pinterest.com Mary Ann Melton
spokesman.com
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Modeling approach
canada-hunts.ca
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Model K AICc Delta AICc
Model Likelihood
AICc Weight
Log Likelihood
Cumulative Weight
Habitat 4 178.52 0.00 1.00 5.05 -85.26 0.51
Habitat + Intrinsic
5 179.56 1.04 0.60 0.30 -84.77 0.81
Anthro. + Habitat
6 181.38 2.86 0.24 0.12 -84.68 0.93
ALL THREE 7 182.41 3.89 0.14 0.07 -84.19 1.00
Anthro. 3 233.21 54.69 <0.001 <0.001 -113.60 1.00
Anthro + Intrinsic
4 234.24 55.72 <0.001 <0.001 -113.12 1.00
Intrinsic 2 255.05 76.53 <0.001 <0.001 -125.52 1.00
NULL 1 256.68 78.16 <0.001 <0.001 -127.34 1.00
Hypothesis Testing
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Covariate Coefficient Standard Error
Hazard ratio [exp
(coefficient)]
95% Lower Confidence
Limit
95% Upper Confidence
Limit
P-value
Proportion time sage previous winter
10.29 4.13 29,361.60 8.98 96,475,534
0.01
Variation in snow depth previous winter
0.18 0.10 1.20 0.98 1.46 0.08
Total terrain ruggedness for the week
-0.43 0.06 0.65 0.58 0.73 <0.001
Summary of final model
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Schoenfeld Residuals
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Hazard Plots Proportion time in sage the previous winter
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Hazard Plots Variation in snow depth the previous winter
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Hazard Plots Total terrain ruggedness for the week